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license: mit
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---
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license: mit
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name: MPTS-52-CSP
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tags:
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- crystal-generation
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- materials-design
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- materials-discovery
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- structure-prediction
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---
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# Description
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This is an [OMatG (Open Materials Generation)](https://github.com/FERMat-ML/OMatG) model for crystal structure prediction
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(CSP) of inorganic crystals trained on the MPTS-52 (Materials Project Time Splits) dataset.
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This dataset is also included in OMatG.
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The subdirectories in this repository contain various model hyperparameters and training checkpoints for a
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variety of MTPS-52-CSP models.
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# Uses
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The checkpoints and model hyperparameters can be used for prediction of crystalline structures with
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OMatG,
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as described in the [this README.md file](https://github.com/FERMat-ML/OMatG/blob/main/README.md)
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# Recommendations
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The [Linear-ODE checkpoints](https://huggingface.co/OMatG/MPTS-52-CSP/tree/main/Linear-ODE)
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currently provide the best results with respect to structure stability, novelty, and uniqueness.
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# Citation
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Please cite [our paper on OpenReview](https://openreview.net/forum?id=gHGrzxFujU) if using OMatG.
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# Links
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[OMatG on GitHub](https://github.com/FERMat-ML/OMatG): See this repository for OMatG installation, training and usage instructions.
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[KIM Initiative](https://kim-initiative.org/): Knowledgebase of Interatomic Models. Tools and resources for researchers in materials science and chemistry.
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[Fermat-ML on GitHub](https://github.com/FERMat-ML): Foundational Representation of Materials. Machine learning foundation model for materials and chemistry discovery.
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